Exploring daily wind data using the Meteostat

Group Members: Travis, Ira, Micah

Course: Data Science

Goal: Explore and compare wind trends in distinct U.S. regions


Source: Meteostat Python API

Dataset Type: Aggregated weather observations per station

Key Variables
  • wspd: Average wind speed (mph)
  • wdir: Mean wind direction (degrees)
  • tavg: Average air temperature (°F)

Time Period: 2024

Locations: ~30

Frame: Hourly and Daily

Units: Metric (mph, degrees, °F)


#Start of Data ::: {.panel-tabset}

Regional Wind Analysis by Speed and Direction
Hourly Averages 2024 | Data: Meteostat
latitude longitude Wind Statistics
Speed (mph) Direction (°)
Midwest
Cleveland, OH 41.4993 -81.6944 40.1 227.0
Chicago, IL 41.8781 -87.6298 35.4 259.0
Detroit, MI 42.3314 -83.0458 34.8 248.0
Milwaukee, WI 43.0389 -87.9065 33.9 297.0
Minneapolis, MN 44.9778 -93.265 28.2 307.0
Northeast
Buffalo, NY 42.8864 -78.8784 46.0 243.0
Boston, MA 42.3601 -71.0589 38.2 278.0
Philadelphia, PA 39.9526 -75.1652 31.0 297.0
Pittsburgh, PA 40.4406 -79.9959 25.3 299.0
New York, NY 40.7128 -74.006 23.8 300.0
Southeast
Jacksonville, FL 30.3322 -81.6557 32.5 81.0
Miami, FL 25.7617 -80.1918 29.4 81.0
Tampa, FL 27.9506 -82.4572 26.0 49.0
Charlotte, NC 35.2271 -80.8431 22.7 319.0
Atlanta, GA 33.749 -84.388 17.8 357.0
West
Denver, CO 39.7392 -104.9903 30.2 180.0
San Francisco, CA 37.7749 -122.4194 29.9 294.0
Los Angeles, CA 34.0522 -118.2437 24.6 208.0
Portland, OR 45.5152 -122.6784 24.4 333.0
Seattle, WA 47.6062 -122.3321 18.6 191.0
Legend: 🔵North 🔴East 🟡South 🟢West | Darker = Stronger




  1. How do wind patterns change by region?

  2. What are some case studies of extreme weather?

  3. How do geographical features (lakes, oceans, mountains, deserts, plains) impact wind patterns?